1. Field of the Invention
The present invention relates to OFDM (Orthogonal Frequency Division Multiplexing), MIMO (Multiple Input, Multiple Output) communication. More particularly, the present invention pertains to an EM channel estimation solution that requires relatively low computational complexity, while remaining relatively effective in providing channel state information estimates for broadband channels in environments that may suffer from slow fading, fast fading, such as due to user mobility, or both.
2. Background Art
The demand for reliable high speed broadband communication systems with high spectral efficiency is growing rapidly. One type of broadband communication solution that provides a relatively spectral efficiency at relatively high transmission rates and that is resistant to the effects of multipath fading includes using OFDM in combination with multi-carrier space time processing and multiple transmit and multiple receive antennas, commonly referred to as MIMO. MIMO OFDM is a suitable modulation scheme for broadband networks due to its ability to cope with multipath fading, and multi-carrier space time processing allows multi-transmit and multi-receive communication through the use of multiple parallel sub-channels at high data rates that can provide diversity gain and spatial multiplexing gain.
OFDM is commonly known solution that is resistant to multipath fading and has been implemented in a variety of wireless standards, including IEEE 802.16 for Wireless Local and Metropolitan Networks, IEEE 802.11 for high speed Wireless Local Area Networks (WLAN), and Digital Video Broadcasting (DVB). The IEEE 802.16-2004 standard is primarily intended for fixed wireless systems, and the 802.16e amendment is intended for both fixed and mobile wireless systems. The IEEE 802.11 Working Group has adopted the amendment, 802.11n, which adds multiple transmit and receive antennas for increased throughput and spatial diversity.
However, in broadband networks or communication systems that employ MIMO OFDM, channel fading remains a challenging problem when estimating MIMO channels. Currently known channel estimation techniques are relatively complex and use training sequences in a relatively inefficient manner. For example, one class of channel estimation technique includes using a preamble structure where the first OFDM block sent is composed of a training block. The training block can be composed of a number of pilot symbols on selected subcarriers while the rest can be set to zero. The frequency response of the remaining subcarriers can then be interpolated by first obtaining an initial channel estimate, finding a time-domain channel estimate, windowing significant taps, and converting back to the frequency-domain and replacing the values of the known subcarriers by the initial estimate. This pilot-assisted class of channel estimation method is further disclosed by M. Belotserkovsky, in the prior art reference entitled, “An equalizer initialization algorithm for OFDM receivers”, Digest of Technical Papers, International Conference on Consumer Electronics, 2002; and by Jiun Siew, Robert Piechocki, Andrew Nix, and Simon Armour, in another prior art reference entitled, “A channel estimation method for MIMO-OFDM Systems”, Proceedings of the London Communications Symposium, pp. 372-373, 2002.
Another class of channel estimation techniques may be performed by periodically transmitting training blocks or sequences, such as at the start of each frame. This class of channel estimation techniques sometimes use an EM (Expectation and Maximization)-based approach, and which include techniques further disclosed by Meir Feder and Ehud Weinstein in their prior art reference entitled, “Parameter Estimation of Superimposed Signals Using the EM Algorithm,” IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 36, No. 4, April 1988; by Laurent Mazet, Veronique Buzenac-Settineri, Marc de Courville, and Pierre Duhamel in their prior art reference entitled, “EM-based Semi-Blind Estimation of Time-Varying Channels,” IEEE Workshop on Signal Processing Advances in Wireless Communications, 2003; by X. Zhuang and F. Vook in their prior art reference entitled, “Iterative Channel estimation and decoding for a turbo-coded OFDM system via the EM algorithm,” IEEE International Conference on Acoustics, Speech, and Signal Processing, Orlando, USA, May 2002; by Waleed M. Younis and Ali H. Sayed in their prior art reference entitled, “Efficient Adaptive Receivers for Joint Equalization and Interference Cancellation in Multiuser Space-Time Block-Coded Systems,” IEEE Transactions on Signal Processing, vol. 51, No. 11, November 2003; by H. Zamiri-Jafarian and S. Pasupathy in their prior art reference entitled, “Recursive Channel Estimation for Wireless Communication via the EM Algorithm,” IEEE International Conference on Personal Wireless Communications, 1997; by Y. Zhao in his prior art reference entitled, “An EM Algorithm for Linear Distortion Channel Estimation Based on Observations from Mixture of Gaussian Sources,” IEEE Trans. on Speech and Audio Processing, Vol. 7, July 1999; and by C. Cozzo and B. Hughes in their prior art reference entitled, “Joint Channel Estimation and Data Symbol Detection in Space-Time Communications,” ICC, Commun. Theory Mini-Symposium, June 2000, and Carlos H. Aldana, and John Cioffi, “Channel Tracking for Multiple Input, Single Output Systems using EM algorithm,” IEEE ICC, vol. 1, 2004. These known EM-based channel estimation techniques, however, are computationally complex, and thus are relatively expensive to design and manufacture.
Consequently, a need exists for a channel estimation solution that is relatively less complex than current solutions, while remaining relatively effective in calculating CSI estimates for channels in environments that may suffer from slow channel fading, fast channel fading, or both.